Sloan Working Papershttp://hdl.handle.net/1721.1/17922018-03-06T19:55:56Z2018-03-06T19:55:56ZAgile for Everyone Else: Using Triggers and Checks to Create Agility Outside of Software DevelopmentRepenning, JamesKieffer, DonaldRepenning, Nelsonhttp://hdl.handle.net/1721.1/1103252017-06-28T06:17:23Z2017-06-27T00:00:00ZAgile for Everyone Else: Using Triggers and Checks to Create Agility Outside of Software Development
Repenning, James; Kieffer, Donald; Repenning, Nelson
2017-06-27T00:00:00ZA new 0-1 formulation of the restricted container relocation problem based on a binary encoding of congurationsGalle, VirgileBarnhart, CynthiaJaillet, Patrickhttp://hdl.handle.net/1721.1/1099782017-10-21T06:18:32Z2017-06-16T00:00:00ZA new 0-1 formulation of the restricted container relocation problem based on a binary encoding of congurations
Galle, Virgile; Barnhart, Cynthia; Jaillet, Patrick
The Container Relocation Problem (CRP), also called Block Relocation Problem (BRP), is concerned with finding a sequence of moves of containers that minimizes the number of relocations needed to retrieve all containers, while respecting a given order of retrieval. The restricted CRP enforces that only containers blocking the target container can be relocated. We improve upon and enhance an existing binary encoding and using it, formulate the restricted CRP as a binary integer programming problem in which we exploit structural properties of the optimal solution. This integer programming formulation reduces significantly the number of variables and constraints compared to existing formulations. Its efficiency is shown through computational results on small and medium sized instances taken from the literature.
Submitted to EJOR June 2017
2017-06-16T00:00:00ZThe Stochastic Container Relocation ProblemGalle, V.Borjian Boroujeni, S.Manshadi, V.H.Barnhart, C.Jaillet, P.http://hdl.handle.net/1721.1/1077622017-10-20T14:51:55Z2017-03-28T00:00:00ZThe Stochastic Container Relocation Problem
Galle, V.; Borjian Boroujeni, S.; Manshadi, V.H.; Barnhart, C.; Jaillet, P.
The Container Relocation Problem (CRP) is concerned with finding a sequence of moves of containers that minimizes the number of relocations needed to retrieve all containers, while respecting a given order of retrieval. However, the assumption of knowing the full retrieval order of containers
is particularly unrealistic in real operations. This paper studies the stochastic CRP (SCRP), which relaxes this assumption. A new multi-stage stochastic model, called the batch model, is introduced, motivated, and compared with an existing model (the online model). The two main contributions are an
optimal algorithm called Pruning-Best-First-Search (PBFS) and a randomized approximate algorithm called PBFS-Approximate with a bounded average error. Both algorithms, applicable in the batch and online models, are based on a new family of lower bounds for which we show some theoretical properties. Moreover, we introduce two new heuristics outperforming the best existing heuristics. Algorithms, bounds and heuristics are tested in an extensive computational section. Finally, based on strong computational evidence, we conjecture the optimality of the “Leveling” heuristic in a special “no information” case, where at any retrieval stage, any of the remaining containers is equally likely to be retrieved next.
2017-03-28T00:00:00ZTechnology Readiness Levels at 40: a study of state-of-the-art use, challenges, and opportunitiesOlechowski, AlisonEppinger, Steven D.Joglekar, Nitinhttp://hdl.handle.net/1721.1/963072015-04-02T06:20:07Z2015-04-01T00:00:00ZTechnology Readiness Levels at 40: a study of state-of-the-art use, challenges, and opportunities
Olechowski, Alison; Eppinger, Steven D.; Joglekar, Nitin
The technology readiness level (TRL) scale was introduced by NASA in the 1970s as a tool for assessing the maturity of technologies during complex system development. TRL data have been used to make multi-million dollar technology management decisions in programs such as NASA's Mars Curiosity Rover. This scale is now a de facto standard used for technology assessment and oversight in many industries, from power systems to consumer electronics. Low TRLs have been associated with significantly reduced timeliness and increased costs across a portfolio of US Department of Defense programs. However, anecdotal evidence raises concerns about many of the practices related to TRLs. We study TRL implementations based on semi-structured interviews with employees from seven different organizations and examine documentation collected from industry standards and organizational guidelines related to technology development and demonstration. Our findings consist of 15 challenges observed in TRL implementations that fall into three different categories: system complexity, planning and review, and validity of assessment. We explore research opportunities for these challenges and posit that addressing these opportunities, either singly or in groups, could improve decision processes and performance outcomes in complex engineering projects.
2015-04-01T00:00:00Z